Lowering Flu Season’s Heavy Toll

Computational modeling techniques reveal new insights that could help minimize the annual costs of influenza.

As year-end activities ramp up, the flu is in full swing. In a season that’s often filled with social and economic pressures, the added price of influenza can be staggering: up to $87B in medical costs and lost productivity according to the latest Centers for Disease Control (CDC) statistics.

But research by investigators at the Biocomplexity Institute of Virginia Tech is informing new policies that could help lift the heavy toll of flu season.

Previous studies by Professor Achla Marathe and Research Scientist Jiangzhuo Chen of the institute’s Network Dynamics and Simulation Science Laboratory have highlighted paid sick leave as an effective way to halt the spread of flu in the workplace.

While absenteeism caused by flu-related illness takes a heavy toll, the reverse can cause even worse damage. When sick workers feel compelled to come to work, they tend to increase rates of infection among their co-workers, ultimately costing the company more money than if they had stayed home: up to $16.3B in lost earnings.

But there is another important piece to the flu puzzle: prevention. Vaccine effectiveness varies in any given year—because the virus mutates quickly it’s often difficult to predict which strains will be the most widely spread. But CDC studies show that the flu vaccine can reduce the overall threat to the population by about 50-60% in any given season when properly matched with the predominant strain.

Marathe and her research team in the Network Dynamics and Simulation Science Laboratory have been trying to understand not only how paid sick leave might play a role in mediating infectious disease, but also the most effective way to allocate vaccinations.

In particular, their study tracks efficiency and fairness—two important factors that are often at odds with one another when decisions are made about vaccine distribution. However, effective distribution scenarios must take both factors into account.

Published in Value in Health, Marathe’s research explores a variety of scenarios via agent-based modeling to uncover the most effective scenario for eradicating flu. While it’s fairest to widely distribute the flu vaccine to all, such a scheme may not be the most efficient way of mediating or eradicating a flu epidemic.

To understand how disease spreads through a network of social contacts, the researchers used a simulation tool called EpiFast to model an epidemic of a flu-like illness on through a simulated social network modeled on Montgomery County in Southwest Virginia. Each person in the county was represented in the model by a statistically accurate ‘agent’ in order to produce a realistic simulation of the entire population at scale.

A Susceptible-Exposed-Infectious-Recovered (SEIR) model was applied to understand the flow of infection within individuals and between their social contacts. The model accounts for symptomatic and asymptomatic health states of the individuals. It also accounts for the latency period between initial infection and the actual infectious state.

A variety of scenarios were employed to understand the interplay between fairness and efficiency. When attempting to assess the best distribution method for a limited supply of vaccines, public health officials often wonder whether to vaccinate based on age, household size, vulnerability, or connectivity within a social network, among many other variables.

Although a social connectivity-based strategy gives the best results, both in terms of efficiency and fairness, researchers realize that it may be difficult to measure for every individual in the population and hence difficult to implement for policy makers. Among demographics-based strategies, the study found that a mixed-principle strategy for distributing limited vaccines was the best. That is, if younger members of large households were vaccinated first, prevalence rates could be dropped to the lowest levels and 80% fairness in vaccine distribution could still be achieved.

Realistic simulation platforms, combined with practical scenarios pertaining to diseases and interventions, can help inform public health officials and decision-makers about the pros and cons of policies before they are implemented, ultimately saving lives and tax dollars. With better strategies in place, the next flu season could prove to be far less costly.